Metabolic reprogramming and therapeutic resistance in primary and metastatic breast cancer
Molecular Cancer,
Год журнала:
2024,
Номер
23(1)
Опубликована: Ноя. 21, 2024
Metabolic
alterations,
a
hallmark
of
cancer,
enable
tumor
cells
to
adapt
their
environment
by
modulating
glucose,
lipid,
and
amino
acid
metabolism,
which
fuels
rapid
growth
contributes
treatment
resistance.
In
primary
breast
metabolic
shifts
such
as
the
Warburg
effect
enhanced
lipid
synthesis
are
closely
linked
chemotherapy
failure.
Similarly,
metastatic
lesions
often
display
distinct
profiles
that
not
only
sustain
but
also
confer
resistance
targeted
therapies
immunotherapies.
The
review
emphasizes
two
major
aspects:
mechanisms
driving
in
both
how
unique
environments
sites
further
complicate
treatment.
By
targeting
vulnerabilities
at
stages,
new
strategies
could
improve
efficacy
existing
provide
better
outcomes
for
cancer
patients.
Язык: Английский
Predicting lymphoma prognosis using machine learning-based genes associated with lactylation
Translational Oncology,
Год журнала:
2024,
Номер
49, С. 102102 - 102102
Опубликована: Авг. 14, 2024
Lactylation,
a
newly
discovered
PTM
involving
lactic
acid,
is
linked
to
solid
tumor
proliferation
and
metastasis.
Lymphoma
patients
exhibit
high
acid
levels,
yet
lactylation's
role
in
lymphoma
underexplored.
This
study
aimed
identify
lactylation-related
genes
using
databases
assess
their
predictive
value
patient
prognosis
through
cell
experiments
clinical
specimens.
Язык: Английский
Spatial transcriptomics reveals prognostically LYZ+ fibroblasts and colocalization with FN1+ macrophages in diffuse large B-cell lymphoma
Cancer Immunology Immunotherapy,
Год журнала:
2025,
Номер
74(4)
Опубликована: Фев. 25, 2025
Diffuse
large
B-cell
lymphoma
(DLBCL)
is
a
clinically
heterogeneous
malignancy
with
diverse
patient
outcomes,
largely
influenced
by
the
tumor
microenvironment
(TME).
Understanding
roles
of
fibroblasts
and
macrophages
within
TME
essential
for
developing
personalized
therapeutic
strategies
in
DLBCL.
This
study
multi-omics
approach,
integrating
spatial
transcriptomics
(n
=
11),
bulk
2,499),
immunohistochemistry
(IHC,
n
37),
multiplex
immunofluorescence
(mIF,
56),
plasma
samples
240)
to
identify
characterize
fibroblast
tumor-associated
macrophage
subtypes
TME.
Hub
genes
LYZ+
FN1+
were
selected
through
univariate
Cox
regression
random
forest
analyses.
Their
prognostic
significance
was
validated
using
IHC,
mIF,
autoantibody
assays
DLBCL
patients
treated
R-CHOP
non-small
cell
lung
cancer
(NSCLC)
receiving
immune
checkpoint
inhibitors
(ICIs).
Fibroblasts
classified
into
two
distinct
subtypes.
Patients
higher
infiltration
demonstrated
superior
prognosis,
which
associated
increased
macrophages.
Key
hub
identified
included
LYZ,
ANPEP,
CSF3R,
C15orf48,
LILRB4,
CLEC7A,
COL7A1,
while
COL1A1,
FN1,
APOE,
DCN,
MMP2,
SPP1,
COL3A1,
COL1A2.
Independent
markers
NSCLC
ICIs
identified,
including
LYZ
LILRB4
at
both
protein
mRNA
levels,
COL1A2
autoantibodies
(p
<
0.05).
In
R-CHOP,
FN1
levels
also
ICIs,
COL3A1
marker
prognostically
relevant
The
these
represent
potential
biomarkers,
providing
insights
improving
outcomes
Язык: Английский
Identification of intratumoral microbiome-driven immune modulation and therapeutic implications in diffuse large B-cell lymphoma
Cancer Immunology Immunotherapy,
Год журнала:
2025,
Номер
74(4)
Опубликована: Март 3, 2025
Diffuse
large
B-cell
lymphoma
(DLBCL)
is
the
most
common
subtype
of
non-Hodgkin
lymphoma,
with
significant
clinical
heterogeneity.
Recent
studies
suggest
that
intratumoral
microbiome
may
influence
tumor
microenvironment,
affecting
patient
prognosis
and
therapeutic
responses.
This
study
aims
to
identify
microbiome-related
subtypes
in
DLBCL
assess
their
impact
on
prognosis,
immune
infiltration,
sensitivity.
Transcriptomic
data
from
48
patients
were
obtained
public
databases.
Consensus
clustering
was
used
classify
into
distinct
subtypes.
Functional
enrichment
analysis,
infiltration
assessments,
single-cell
RNA
sequencing
performed
explore
biological
characteristics
these
Drug
sensitivity
predictions
made
using
OncoPredict
tool.
Hub
genes'
expression
function
validated
inferred
cell
lines
independent
cohorts
DLBCL.
Two
identified.
Patients
Cluster
1
exhibited
significantly
better
overall
survival
(P
<
0.05),
higher
regulatory
T
cells
M0
macrophages
compared
2,
which
associated
poorer
outcomes.
analysis
revealed
genes
involved
pathways,
including
cytokine-cytokine
receptor
interactions
chemokine
signaling,
suggesting
enhanced
anti-tumor
In
contrast,
2
enriched
immunosuppressive
contributing
a
less
favorable
prognosis.
Single-cell
heterogeneity
populations
within
microenvironment.
B
notable
heterogeneity,
as
indicated
by
stemness
differentiation
potential
scoring.
Intercellular
communication
demonstrated
played
key
role
interactions,
differences
observed
MIF
signaling
between
subgroups.
Pseudo-time
further
trajectories
cells,
highlighting
across
different
environments.
Metabolic
pathway
showed
average
levels
metabolic
pathways
among
subgroups,
functional
specialization.
Furthermore,
interaction
core
microbiome-driven
differentially
expressed
identified
nine
(GSTM5,
LURAP1,
LINC02802,
MAB21L3,
C2CD4D,
MMEL1,
TSPAN2,
CITED4),
found
play
critical
roles
influenced
microbiome.
MMEL1
CITED4
important
biologically
classification.
demonstrates
prognostic
significance
DLBCL,
identifying
activity,
The
findings
provide
insights
focusing
dynamics.
These
results
lay
foundation
for
microbiome-based
biomarkers
personalized
treatment
approaches,
ultimately
aiming
enhance
outcomes
Язык: Английский
Single-cell RNA sequencing in diffuse large B-cell lymphoma: tumor heterogeneity, microenvironment, resistance, and prognostic markers
Frontiers in Oncology,
Год журнала:
2025,
Номер
15
Опубликована: Апрель 9, 2025
Diffuse
large
B-cell
lymphoma
(DLBCL)
is
a
highly
heterogeneous
malignancy
with
challenges
in
treatment
resistance
and
relapse.
Single-cell
RNA
sequencing
(scRNA-seq)
has
provided
important
insights
into
tumor
heterogeneity,
microenvironment
interactions,
mechanisms,
prognostic
biomarkers.
This
review
summarizes
key
findings
from
scRNA-seq
studies,
which
have
deepened
our
understanding
of
DLBCL
contributed
to
the
development
precision
therapeutic
strategies.
Integrating
spatial
transcriptomics
single-cell
multi-omics
may
further
elucidate
disease
mechanisms
identify
novel
targets,
supporting
advancement
medicine
DLBCL.
Язык: Английский
Tumor Biology Hides Novel Therapeutic Approaches to Diffuse Large B-Cell Lymphoma: A Narrative Review
International Journal of Molecular Sciences,
Год журнала:
2024,
Номер
25(21), С. 11384 - 11384
Опубликована: Окт. 23, 2024
Diffuse
large
B-cell
lymphoma
(DLBCL)
is
a
malignancy
of
immense
biological
and
clinical
heterogeneity.
Based
on
the
transcriptomic
or
genomic
approach,
several
different
classification
schemes
have
evolved
over
years
to
subdivide
DLBCL
into
clinically
(prognostically)
relevant
subsets,
but
each
leaves
unclassified
samples.
Herein,
we
outline
tumor
biology
behind
actual
potential
drug
targets
address
challenges
drawbacks
coupled
with
their
(potential)
use.
Therapeutic
modalities
are
discussed,
including
small-molecule
inhibitors,
naked
antibodies,
antibody-drug
conjugates,
chimeric
antigen
receptors,
bispecific
antibodies
T-cell
engagers,
immune
checkpoint
inhibitors.
Candidate
drugs
explored
in
ongoing
trials
diverse
toxicity
issues
refractoriness
drugs.
According
literature
DLBCL,
promise
for
new
therapeutic
lies
epigenetic
alterations,
receptor
NF-κB
pathways.
present
putative
hiding
lipid
pathways,
ferroptosis,
gut
microbiome
that
could
be
used
addition
immuno-chemotherapy
improve
general
health
status
patients,
thus
increasing
chance
being
cured.
It
may
time
devote
more
effort
exploring
metabolism
discover
novel
druggable
targets.
We
also
performed
bibliometric
knowledge-map
analysis
published
from
2014-2023.
Язык: Английский
Spatial transcriptomics unveils immune cellular ecosystems associated with patient survival in diffuse large B-cell lymphoma
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 16, 2024
Summary
Diffuse
Large
B-cell
Lymphoma
(DLBCL)
is
the
most
prevalent
subtype
of
non-Hodgkin’s
lymphoma
for
which
current
therapeutic
strategies
remain
insufficient.
The
diffuse
nature
DLBCL,
lacking
distinct
tissue
structures,
represents
a
challenge
to
elucidate
cellular
organization
and
interactions
within
tumor
microenvironment
(TME).
In
this
study,
we
applied
spatial
transcriptomics
identify
spatially-resolved
gene
expression
profiles
in
10
DLBCL
samples,
identifying
immune
cell
infiltration
colocalization
patterns.
These
were
classified
into
six
ecosystems
(Cell-Eco)
that
differ
composition,
functional
patterns,
neighborhood
characteristics.
Cell-Eco
signatures
provided
prognostic
scores
stratified
patients
with
different
overall
survival
rates.
We
also
found
C1q+
tumor-associated
macrophages
are
primary
cells
interacting
malignant
B
influencing
architecture
TME.
This
study
provides
novel
biological
insights
complexity
TME
highlights
potential
value
its
organization.
Graphical
abstract
Key
findings
Spatial
classifies
tissues
based
on
consists
transcriptomic
Spatially-resolved
stratify
survival.
primarily
interact
contribute
microenvironment.
Язык: Английский